import collections


def topKFrequent(nums, k):
    def sift_down(arr, root, k):
        """下沉log(k),如果新的根节点>子节点就一直下沉"""
        val = arr[root]  # 用类似插入排序的赋值交换
        while root << 1 < k:
            child = root << 1
            # 选取左右孩子中小的与父节点交换
            if child | 1 < k and arr[child | 1][1] < arr[child][1]:
                child |= 1
            # 如果子节点<新节点,交换,如果已经有序break
            if arr[child][1] < val[1]:
                arr[root] = arr[child]
                root = child
            else:
                break
        arr[root] = val

    def sift_up(arr, child):
        """上浮log(k),如果新加入的节点<父节点就一直上浮"""
        val = arr[child]
        while child >> 1 > 0 and val[1] < arr[child >> 1][1]:
            arr[child] = arr[child >> 1]
            child >>= 1
        arr[child] = val

    stat = collections.Counter(nums)
    stat = list(stat.items())
    heap = [(0, 0)]
    # 构建规模为k+1的堆,新元素加入堆尾,上浮
    for i in range(k):
        heap.append(stat[i])
        sift_up(heap, len(heap) - 1)
        # 维护规模为k+1的堆,如果新元素大于堆顶,入堆,并下沉
    for i in range(k, len(stat)):
        if stat[i][1] > heap[1][1]:
            heap[1] = stat[i]
            sift_down(heap, 1, k + 1)
    return [item[0] for item in heap[1:]]


s = input().split(" ")
n = int(s[0])
k = int(s[1])
nums = [int(x) for x in input().split()]
print(topKFrequent(nums, k))
